Nowadays, various memory-hungry applications like machine learning algorithms are knocking "the memory wall". Toward this, emerging memories featuring computational capacity are foreseen as a promising solution that performs data process inside the memory itself, so-called computation-in-memory, while eliminating the need for costly data movement. Recent research shows that utilizing the custom extension of RISC-V instruction set architecture to support computation-in-memory operations is effective. To evaluate the applicability of such methods further, this work enhances the standard GNU binary utilities to generate RISC-V executables with Logic-in-Memory (LiM) operations and develop a new gem5 simulation environment, which simulates the entire system (CPU, peripherals, etc.) in a cycle-accurate manner together with a user-defined LiM module integrated into the system. This work provides a modular testbed for the research community to evaluate potential LiM solutions and co-designs between hardware and software.

翻译：当前，诸如机器学习算法等各类内存密集型应用正持续冲击"存储墙"瓶颈。为此，具备计算能力的新兴存储器被视为一种有前景的解决方案——它能在存储体内部直接执行数据处理（即存内计算），从而消除昂贵的数据搬运开销。最新研究表明，利用RISC-V指令集架构的自定义扩展支持存内计算操作具有显著效果。为深入评估此类方法的适用性，本研究对标准GNU二进制工具进行增强，使其能够生成包含逻辑存内操作（LiM）的RISC-V可执行文件，并开发了新型gem5仿真环境。该环境以周期精确方式模拟包含CPU、外设等在内的完整系统，同时集成用户自定义的LiM模块。本工作为研究社区提供了一个模块化测试平台，用于评估潜在LiM解决方案及软硬件协同设计方案。